APAC

Artificial Intelligence and Machine Learning in Real Estate

Long tipped as a revolutionary technology of the future, Artificial Intelligence has already begun to reshape the way work is carried out in commercial real estate: chat bots are changing the way real estate services are delivered; recommendation engines are revolutionising the way we find property and automated – and more efficient – ways of tracking and analysing mountains of unstructured data are unlocking new opportunities for value.

Find out more about how AI is reshaping the way work is carried out today – and will be carried out in the future.

Conversational Machines – the ‘Chat Bots’

Facebook now has ‘chat bots’ as an embedded part of its Messenger app, where you can ‘converse’ to receive news updates, order food, flowers or taxis.

x.ai offers an AI personal assistant who schedules meetings for you with the other participants via email. The company says it could save you 1,800 hours a year.

Corporations such as the UK’s British Gas, Royal Bank of Canada and Singapore’s DBS Bank are already testing chat bot customer services and seeing large cost efficiency savings compared to telephone helplines.

IN REAL ESTATE TOMORROW

Automated email marketing enquiries and even leasing proposals could be undertaken by machines. Questions about the specification or services could be responded to conversationally as part of any email chain.

Residential real estate services Trulia in the US and Sevi in Singapore are just two companies with Facebook Messenger bots where users message the bot with their property needs and the bot serves up listings, summaries and images.

Facilities management providers are investigating chat bots as customer service agents. Bots remove any concerns around consistency or capacity illness and can significantly reduce costs once deployed.

The Right Recommendations

THE TECH TODAY

Around 75% of all the movies and programmes watched on Netflix are selected through the on-screen recommendations system, an AI engine itself.

Software is increasingly drawing on big data to learn from the behaviour of millions of users worldwide, gathering a vast data set that can be used for further improved future recommendations.

IN REAL ESTATE TOMORROW

Better recommendations for property are expected to come through a broader dataset of information about the individual or organisation seeking real estate. A corporate occupier profile could include information about their industry sector, competitors, revenue trends, or profitability – including broader aspects than the conventional requirement scope.

Combining improved insights aims to swing the balance away from the current listings approach and towards a more tailored list of recommendations based on an informed review of the current availability.

Understanding Unstructured Data

THE TECH TODAY

Contracts are often stored as scanned documents by their holders – these being traditionally unreadable by computers. ‘Hidden’ data incurs costs, in lost hours spent searching through documents and the risks of the unknown.

The ‘LegalTech’ arena already leads the field in the AI technologies for automated reading, analysis and extraction. AI systems can be used to extract and codify contract clauses, connect documents with amendments and identify missing documentation.

IN REAL ESTATE TOMORROW

The automation and efficiency of lease data collection, abstraction and management will be significantly improved, with costs reduced accordingly. This is already a reality and will be adopted more widely in the near future.

Analysing leases could identify areas of risk where key lease terms have perhaps been omitted and leave the occupier vulnerable.

The increased reporting requirements under the upcoming FASB / IFRS 16 regulations exacerbate the need for accurate and up-to-date logging of all lease documentation. AI technologies could be used for the extraction of relevant lease clauses and automatic consolidation into financial statements and reports.

Rob Parker is Senior Portfolio Manager in Cushman & Wakefield’s Global Occupier Services team, based in Singapore. Rob works with major corporate clients and writes on emerging technologies and digital disruption, including blockchain and the gig economy.